Demand Forecaster

This tool uses statistical methods from actual demand planning practice — no black boxes, no assumptions baked in. Everything is calculated from your data.

Linear Regression (Trend Detection)

The tool fits a least-squares regression line to your historical data. The slope of this line is your organic monthly growth rate — positive means growing, negative means declining. This is used as the baseline for all three forecast scenarios.

Seasonality Index

Each month's seasonality index is the ratio of its actual value to the trend-line value at that point, normalised so the average index = 1.0. An index of 1.3 means that month typically runs 30% above the trend — capturing real patterns from your own data rather than generic assumptions.

Three Scenarios

• Conservative — Trend line only. Best for pessimistic planning and minimum inventory requirements.
• Moderate — Trend × seasonality index. The most realistic scenario for standard inventory planning.
• Aggressive — Trend × seasonality × small compounding growth factor. Useful for capacity planning and upper-bound buffer stock calculations.

Anomaly Detection

Months where actual sales deviate more than 2 standard deviations from the trend line are flagged as anomalies. These often represent flash sales, stockouts, or external disruptions — and knowing about them helps you avoid letting outliers skew your forecast.

How Nventory Helps

Nventory tracks your sales velocity across every channel in real time and generates demand forecasts automatically. Instead of maintaining spreadsheets, Nventory surfaces reorder recommendations, flags seasonal trends, and helps you plan purchasing decisions with confidence — reducing both stockouts and excess inventory carrying costs.